515Animal Biodiversity and Conservation 27.1 (2004) © 2004 Museu de Ciències NaturalsISSN: 1578–665X

A Bayesian approach to combining animal abundance and demographic data. — In studies of wild animals, one frequently encounters both count and mark–recapture–recovery data. Here, we consider an integrated Bayesian analysis of ring–recovery and count data using a state–space model. We then impose a L...

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Bibliographic Details
Main Author: Demographic Data Animal Biodiversity
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Subjects:
Key words
Census data
Integrated analysis
Kalman filter
Logistic regression
Ring–recovery data
State– space model
Vanellus vanellus
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.469.3741
http://www.bcn.cat/museuciencies_fitxers/imatges/FitxerContingut4563.pdf
Description
Summary:A Bayesian approach to combining animal abundance and demographic data. — In studies of wild animals, one frequently encounters both count and mark–recapture–recovery data. Here, we consider an integrated Bayesian analysis of ring–recovery and count data using a state–space model. We then impose a Leslie– matrix–based model on the true population counts describing the natural birth–death and age transition processes. We focus upon the analysis of both count and recovery data collected on British lapwings (Vanellus vanellus) combined with records of the number of frost days each winter. We demonstrate how the combined analysis of these data provides a more robust inferential framework and discuss how the Bayesian approach using MCMC allows us to remove the potentially restrictive normality assumptions commonly assumed for analyses of this sort. It is shown how WinBUGS may be used to perform the Bayesian analysis. WinBUGS code is provided and its performance is critically discussed.

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